In order to investigate the interaction effect of nitrogen (N) and sulfur (S) fertilizer on dry matter accumulation and grain yield of winter wheat in eastern Hebei Province, a winter wheat Shinong 952 was used as material. A split plot design was adopted, with the N application as main plot: 0 kg·hm^-2 (N0), 180 kg·hm^-2 (N1), 240 kg·hm^-2 (N2) and 300 kg·hm^-2 (N3), and S application as the sub-plot:82.5 kg·hm^-2 (S1), 112.5 kg·hm^-2 (S2), 142.5 kg·hm^-2 (S3) and 172.5 kg·hm^-2 (S4). The differences of chlorophyll relative content (SPAD), leaf area index (LAI), dry matter and nitrogen translocation, and grain yield of winter wheat under different treatments were analyzed. The results showed that N and S application significantly affected LAI and flag leaf SPAD of winter wheat. The SPAD value of N1S2 treatment was the highest at anthesis, which was significantly higher than the other treatments except N2S2 and N3S2. The N and S application had positive effects on the translocation of dry matter and nitrogen restored before anthesis, and the accumulation of dry matter and nitrogen after anthesis, the interaction between N and S nutrition also was significant. Wheat grain yield ranged from 7 364.71 kg·hm^-2 to 10 078.20 kg·hm^-2 under different treatments, and increased significantly with the increase of N application amount. The grain yield of N2S3 treatment was significantly higher than the treatments under N0 and N1 levels, but was no significantly different from the other treatments under N2 and N3 levels. S application had no significant effect on grain yield and 1 000-grain weight of wheat. Overall, the application of nitrogen-sulfur fertilizer with right amounts is conducive to higher SPAD values and LAI in the flag leaves of winter wheat, can enhance the photosynthetic capacity of the leaves, promote post-anthesis dry matter accumulation and pre-anthesis nitrogen translocation, and ultimately increase winter wheat yield. 240 kg N·hm^-2 and 82.5 kg S·hm^-2 were the most suitable N and S fertilizer combinations for saving fertilizer and increasing efficiency in winter wheat production.

To investigate the effect of phosphorus application mode on the grain setting characteristics of wheat ears under late spring coldness, wheat varieties Xinmai 26 with weak resistance to late spring coldness and Yannong 19 with strong resistance to late spring coldness were selected as experimental materials from 2022 to 2023. Field pot planting was adopted, and a low temperature light incubator was used to simulate late spring coldness. The main stem and grain setting characteristics of two wheat varieties were analyzed under the treatments of full basal application of phosphorus fertilizer under conventional temperature, 50% of phosphorus fertilizer postpone under conventional temperature, full basal application of phosphorus fertilizer under late spring coldness, and 50% of phosphorus fertilizer postpone under late spring coldness. The results showed that compared with normal temperature, the late spring coldness significantly reduced the number of grains and weight per spike in the main stem of Xinmai 26 and Yannong 19, with a decrease rate of 25.63% and 23.43%, respectively, and a decrease rate of 26.74% and 20.65% in weight per spike, respectively. Among them, the number of grains in the lower spikelets of both varieties decreased the most (40.21% and 31.91%, respectively). The grain position with the largest decrease in grain number was the third and fourth grain positions (40.00% and 80.77%, respectively). Under normal temperature conditions, after applying phosphorus fertilizer, the single spike weight of the main stem of the two varieties was higher than that of the full basal phosphorus fertilizer, with an increase rate of 9.37% and 19.48%, respectively, and the number of grains was increased by 11.17% and 8.45%, respectively. The largest increase in grain number was observed in the lower and upper spikelets (with increase rate of 30.93% and 31.25%, respectively). The thousand-grain weight of Yannong 19 significantly increased (with an increase rate of 12.49%). Compared with the full basal application of phosphorus fertilizer, the postpone of phosphorus fertilizer significantly increased the number of grains and weight per spike in the main stem of two varieties under the risk of late spring coldness. The increase rate of grain number per spike was 22.53% and 14.20%, and the increase rate of grain weight per spike was 25.94% and 10.96%, respectively. The highest increase in grain number in Xinmai 26 was observed in the lower spikelet and the third grain position (with an increase rate of 101.72% and 42.86%, respectively); The spikelet position with the largest increase in grain number of Yannong 19 was the upper spikelet (with an increase rate of 73.68%). In summary, late spring coldness can reduce the number of grains and weight per spike in the main stem of wheat. After applying phosphorus fertilizer, applying phosphorus postpone can alleviate the impact of late spring coldness on wheat spike fruiting by increasing the number of grains and weight per spike in the main stem.

To investigate the effects of nitrogen reduction combined with application of arbuscular mycorrhizal fungi (AMF) on the growth characteristics, photosynthetic physiology, nitrogen metabolism process, and yield of wheat during the grain-filling stage under water-saving irrigation, a wheat line Landa 211 was used as the experimental material. Two irrigation amounts (normal irrigation of 400 mm, water-saving irrigation of 280 mm) and three nitrogen application levels［conventional nitrogen application (250 kg·hm^-2), reduced 20% nitrogen fertilizer application (200 kg·hm^-2), and reduced 40% nitrogen fertilizer application (150 kg·hm^-2)］ were set up, inoculated with the AMF strain Funneliformes mosesae（FM） and no inoculation. The results indicated that FM could infect wheat roots and formed a stable symbiotic relationship. Compared with normal irrigation, the mycorrhizal infection rate, arbuscular growth rate, number of invasion points, and number of vesicles of FM decreased under water-saving irrigation. Compared with the conventional nitrogen application treatment under normal irrigation, reduced 20% nitrogen under water-saving irrigation and inoculation with FM treatment had no significant effect on the dry matter accumulation and leaf area of wheat population, but the plant height and total stem number of the population decreased. The chlorophyll content, chlorophyll fluorescence parameters, and gas exchange parameters of wheat showed no significant differences compared to the conventional nitrogen application treatment under normal irrigation, but were significantly higher than reduced 40% nitrogen treatments under water-saving irrigation and FM inoculation. Compared with the conventional nitrogen application treatment under normal irrigation, there was no significant difference in the total nitrogen content, free amino acid content, soluble protein content of wheat flag leaves, and the activities of nitrate reductase, glutamine synthase, glutamic pyruvate transaminase, and glutamic acid synthase under reduced 20% nitrogen with water-saving irrigation and FM inoculation. The wheat yield under water-saving irrigation and reduced 20% nitrogen combined with FM treatment reached 7 786.0 kg·hm^-2, which was not significantly different from the yield under normal irrigation with conventional nitrogen application. To conclude, reduced 20% nitrogen and applying FM in combination with water-saving irrigation could maintain the chlorophyll content and photosynthesis of wheat during the grain-filling period, and maintain the activity of wheat nitrogen metabolism enzymes and metabolite content, which was a green water and fertilizer management model for water-saving, fertilizer saving, and high-yield maintenance in arid irrigation areas.

To explore the effects of biochar application rates under rotary tillage and deep loosening conditions on winter wheat yield and carbon and nitrogen status in soil, a two-factor randomized block experiment was set up by establishing two tillage methods (rotary tillage and deep loosening) and three biochar application rates of 0, 4.5, and 9 t·hm^-2. The differences in winter wheat yield and soil carbon and nitrogen were comparatively analyzed among different treatments. The results indicated that both tillage method and biochar application rate had significant impact on soil nitrate nitrogen residue, total carbon, total nitrogen, and microbial biomass carbon and nitrogen content in wheat field. The interaction between the two factors reached significant levels for soil total nitrogen and microbial carbon in both 2022 and 2023. In the 0-20 cm soil layer, compared to rotary tillage, deep loosening increased soil total carbon content and total nitrogen content by 13.9% and 29.5%, respectively. Additionally, deep loosening promoted the microbial carbon and nitrogen content in the 20-30 cm soil layer, leading to a significant decrease in soil nitrate nitrogen residue by 8.5%. Compared to no biochar application, the application of biochar had a promoting effect on the microbial carbon and nitrogen content in the 0-30 cm soil layer. It also reduced soil nitrate nitrogen residue in the 0-50 cm soil layer, with total carbon and total nitrogen content increased by 22.4% and 6.7%, respectively. In 2022 and 2023, winter wheat yield significantly increased under deep loosening compared to that under rotary tillage, with increase rate of 15.8% and 12.0%, respectively. Among them, the deep loosening with 9 t hm^-2 biochar application had the highest yield. Comprehensive analysis indicated that deep loosening combined with 9 t·hm^-2 biochar had the best effect, serving as a cultivation and biochar application combination for high yield and improved soil fertility, which is suitable for application and promotion.

Estimation of the leaf water content (LWC) plays an important role in field irrigation management. This study aimed to estimate the LWC of winter wheat based on hyperspectral data of leaf blades, especially focusing on the effect of different variable screening methods and growth stages on the estimation model. Research data were obtained from field trials in 2022 and 2023 at the booting, heading, and grain-filling stages. Vegetation indices were constructed for each growth stage by combining the two bands. Tthe input characteristic variables based on vegetation indices were screened by two methods: (I) the input characteristic variables were directly obtained by ranking the correlation coefficients; (II) based on the method I, the vegetation index was further screened by the ReliefF algorithm to obtain a second set of input characteristic variables. The LWC estimation models were constructed using random forest (RF), long short-term memory (LSTM) network and back propagation neural network (BPNN) based on particle swarm optimization (PSO). The best method for estimating LWC was derived by comparing the accuracy of the models. The results showed that comparing the two variable screening methods, the characteristic variables further screened by ReliefF could effectively improve the accuracy of the LSTM and PSO-BPNN models, while the effect of improving the RF model is not obvious. The best model for each growth stage was established by the ReliefF screening method combined with the PSO-BPNN, at the booting stage, heading stage and grain-filling stage. The r² of the validation set was 0.816, 0.736, and 0.806, respectively, and the RMSE was 0.546%, 0.899%, and 1.531%, respectively, and the NRMSE was 0.681%, 1.195%, and 2.185%, respectively. It was suggested that the screening method of feature variables through the ReliefF algorithm could improve its estimation accuracy in the particular model. Its combination with the PSO-BPNN model had the best application effect in the estimation of LWC in winter wheat at the growth stages.

In order to screen the suitable irrigation amount for strong gluten wheat in the eastern Hebei region in spring, two strong gluten wheat varieties (Zhongmai 886 and Zhongmai 998) were selected as materials, with five irrigation treatments during the jointing and anthesis stages: no irrigation (W₀), 300 m³·hm^-2 (W₁) each time, 450 m³·hm^-2 (W₂) each time, 600 m³·hm^-2 (W₃) each time, and 750 m³·hm^-2 (W₄) each time, the effects of drip irrigation on the SPAD value of flag leaves, dry matter accumulation and transportation, grain filling rate, yield, and yield components of strong gluten wheat were studied. The results showed that with the increase of drip irrigation amount, the SPAD value of flag leaves after anthesis of strong gluten wheat and the duration of grain filling increased. The accumulation and transportation of dry matter and grain yield increased in the range of 0-600 m³·hm^-2, but significantly decreased at 750 m³·hm^-2, while water use efficiency decreased. Under W₃ treatment, the two strong gluten wheat varieties showed the best performance in terms of spike number, grain number per spike, thousand-grain weight, and yield. Taking into account both grain yield and water use efficiency, the optimal drip irrigation amount for strong gluten wheat during jointing and anthesis periods in the eastern Hebei region is 600 m³·hm^-2 each time.

To investigate the water-saving and high-yielding drip irrigation system for spring wheat in the Hetao Irrigation District, a nationally approved spring wheat variety, Bamai 13, was selected as the experimental material. Six drip irrigation frequencies and three drip irrigation levels (300, 450, and 600 m³·hm^-2) were set up in the field, with the conventional furrow irrigation method used by farmers as control. The study focused on the differences in wheat water consumption characteristics, yield formation, and water use efficiency under different drip irrigation frequencies and amounts. The results indicated that the soil evaporation significantly increased from sowing to tillering stage, gradually decreased from tillering to heading stage, and significantly increased from heading to maturity stage. The water consumption during wheat growth stages follows an ascending-descending trend, reaching its maximum from jointing to booting period. With the increase in drip irrigation frequency and water amount, evaporation and water consumption exhibited a gradual upward trend, while wheat yield showed an initial increase followed by a decline. Compared to the control group, low-frequency high-volume drip irrigation significantly reduced soil evaporation and water consumption. Specifically, irrigating six times during the growth period with 300 m³·hm^-2 each time resulted in a 50% reduction in water consumption compared to the control, leading to a significant decrease rate of 26.3% in water usage. Moreover, the yield and water use efficiency was significantly increased by 16.3% and 57.6%, respectively. Therefore, the recommended irrigation regimen for achieving high yield and efficiency in drip-irrigated wheat in the Hetao Irrigation District is six irrigation sessions during the tillering, jointing, booting, flowering, early grain-filling, and mid-grain-filling stages, with 300 m³·hm^-2 of water for each session.

Accurate and effective yield prediction is essential for wheat breeding, cultivation and field management. In this study, the multispectral and RGB images of winter wheat during the grain filling stage were collected from UAV, and 14 spectral traits and 28 morphological traits were extracted as feature variables. Ten machine learning methods, including linear regression, random forest and neural network, were used to construct wheat yield prediction models, and the differences between the models were compared to select the best one. Additionally, machine learning interpretability method SHAP was introduced to analyze the importance of the feature variables, in order to improve the prediction performance of the model. The results showed that among the 10 machine learning methods used, the BPNN model had the best prediction performance (r²=0.826, RMSE=0.094 t·hm^-2). According to the feature importance ranking determined by SHAP, Anthocyanin Reflectance Index (ARI) and Three-Dimensional Canopy Volume (Volume) had the greatest impact on the prediction results, accounting for 45.48% of the total feature importance. After feature selection using SHAP, the BPNN model with the best performance was determined based on nine feature variables (r²=0.865, RMSE=0.075 t·hm^-2). This improved the prediction accuracy compared to the BPNN model using all features and the pre-analysis method Pearson correlation analysis. Therefore, based on the optimal yield prediction model, SHAP mechanism can be used to select and analyze the importance of feature variables, so as to further improve the accuracy of wheat yield prediction.

As a crucial genetic resource, synthetic hexaploid wheat plays a key role in studying of kernel-related traits. In order to further explore the quantitative trait loci (QTL) of kernel-related traits in wheat, a RIL population consisting of 154 lines derived from a cross between XN389 and a synthetic hexaploid wheat (KU2098) was used as materials. Wheat 55K SNP array was used to construct the genetic map and QTLs for nine kernel-related traits were identified, including kernel length (KL), kernel width (KW), kernel area (KA), kernel perimeter (KP), kernel length width ratio (KLWR), thousand-kernel weight (TKW), kernel protein content (KPC), SC (starch content) and wet gluten content (WGC). A total of 84 additive QTLs were identified across 21 wheat chromosomes, except for chromosome 7B. The individual QTL explained the phenotypic variation from 0.91% to 43.41%, with LOD values ranging from 2.54 to 39.96. Among them, 31 major and 10 stable QTLs were identified. A total of twelve QTL clusters, encompassing QTLs associated with kernel-related traits, were identified on chromosomes 1A(1), 1B(1), 1D(1), 2D(1), 4D(1), 5A(1), 5D(1), 6A(2), 6B(2) and 7D(1). In the corresponding physical interval of QTL cluster C8, two candidate genes related to kernel traits were identified. Four candidate genes related to quality traits were identified in physical region of QTL cluster C3. The QTLs can provide reference for yield and quality improvement of wheat.

The middle and lower reaches of Yangtze River is the largest production belt of weak-gluten wheat in China. Due to the humid and rainy weather in the middle and late period of wheat growth, Fusarium head blight (FHB) and powdery mildew (PM) occurre frequently and seriously, and FHB led to the accumulation of DON toxin in pathogen-infected grains. Wheat yellow mosaic virus (WYMV) often happens after a cold winter. These disasters threaten grain yield and food security. Yangmai 15 is an elite weak-gluten and high-yield cultivar bred at the beginning of 21 century, but its comprehensive resistance is weak. To keep the advantages of Yangmai 15 and improve disease resistance, a backcross population was constructed with Yangmai 15 as the recurrent parent, and 92R137(a soft-grain cultivar with high resistances to PM and WYMV) and Ningmai 9(a soft-grain wheat cultivar conferring moderate resistance to FHB) as the donor parents. In lower generations, molecular markers were used to select plants pyramiding PM resistance gene Pm21 and WYMV resistance QTL QYm.nau-2D. In high generations, FHB resistance was evaluated and the key quality indices were tested together with grain yield. Finally, a new weak-gluten and high-yield wheat line Yang 18465 conferring resistance to FHB, PM and WYMV, was bred and introduced to the national wheat regional test in the middle and lower reaches of Yangtze River. The breeding procedures of Yang 18465 will provide a useful reference for the breeding of similar varieties.